Automatic Segmentation of Human Tibial Cartilage

J. Cheong, N. Faggian, D. Suter, and F. Cicuttini (Australia)

Keywords

Segmentation, automatic, cartilage, and osteoarthritis

Abstract

Osteoarthritis is a chronic and crippling disease affecting
an increasing number of people each year. With no known
cure, it is expected to reach epidemic proportions in the
near future. Accurate segmentation of knee cartilage from
magnetic resonance imaging (MRI) scans facilitates the
measurement of cartilage volume present in a patient’s
knee, thus enabling medical clinicians to detect the onset
of osteoarthritis and also crucially, to study its effects.
This paper presents a fully automated method for
segmenting and measuring human tibial cartilage volume
from MRI scans. The method uses a global search
technique developed by Felzenszwalb [1], involving
triangulated polygons as deformable templates to initialise
a patch-based active appearance model (PAAM) [2]. The
cartilage volume obtained from our automatic method is
benchmarked against the current “gold standard”
(cartilage volume measured using manual segmentation)
as well as other semi-automatic methods. The results
obtained are comparable to human manual segmentation.